Abstract 3025: A pooled analysis of lung cancer metabolomics in the Cancer Prevention Studies revealing sphingomyelin (d18:0/22:0) as a potential screening biomarker
Authors: Ziyin Tang, Donghai Liang, Emily L. Deubler, Jeremy A. Sarnat, Sabrina Chow, W.Ryan Diver, Ying Wang
Journal: Cancer Research (2023)

Abstract Background and Purpose: Lung cancer is a heterogeneous disease, often diagnosed at advanced stages, with low overall survival rate. To better understand the lung cancer etiology and discover screening and early detection biomarkers, we performed a nested case-control study to examine the metabolic perturbation related to lung cancer. Methods: This study included 741 case-control pairs (mean age = 67 years) from the ongoing Cancer Prevention Study (CPS) cohorts. Participants completed a comprehensive exposure and health questionnaire at enrollment. Pre-diagnosis blood samples were collected between 1998-2001 in CPS-II and 2006-2013 in CPS-3. Cases and controls were 1:1 matched on date of birth, blood draw date, gender, and race/ethnicity. All eligible controls were cancer-free at the time of case diagnosis. ﻿Odds ratios (ORs) per standard deviation and 95% confidence intervals (CIs) were estimated using conditional logistic regression, controlling for potential confounders including body mass index, fruit and vegetable consumption, smoking status, and hormone use. We further performed stratified analyses by smoking status (never/former/current) and follow-up time (i.e., within 3 years/beyond 3 years between blood draw and diagnosis). Statistical significance was determined as false discovery rate (FDR) &amp;lt; 0.2. Results: Sphingomyelin (d18:0/22:0), a bioactive sphingolipid of cell membranes, was associated with lung cancer risk (OR:1.31, 95% CI: 1.14, 1.51, FDR= 0.18). When stratified by follow-up time, participants diagnosed within 3 years of blood draw had 59% higher risk of lung cancer per standard deviation increase in sphingomyelin (d18:0/22:0) (OR: 1.59, 95% CI: 1.16, 2.16, p = 0.004) and 25% higher risk for those diagnosed beyond 3 years (OR: 1.25, 95% CI: 1.06, 1.47, p = 0.008). Metabolites associated with lung cancer at raw p-value &amp;lt; 0.05 indicated the perturbation mostly in lipid, amino acid, and xenobiotics metabolism. Among lung cancer cases who were never smokers, the extent of lipid and amino acid perturbation appeared to be similar, while among lung cancer cases who were current smokers, lipid metabolism tended to be more prominent. Conclusion: This is the largest prospective study examining lung cancer risk and metabolic response using an untargeted metabolomics platform. These findings provide preliminary support for sphingomyelin (d18:0/22:0) as a potential screening and early detection biomarker for lung cancer. Results also highlight lipid metabolism including sphingolipid and bile acid metabolism may also play an important role in lung cancer etiology. Citation Format: Ziyin Tang, Donghai Liang, Emily L. Deubler, Jeremy A. Sarnat, Sabrina Chow, W.Ryan Diver, Ying Wang. A pooled analysis of lung cancer metabolomics in the Cancer Prevention Studies revealing sphingomyelin (d18:0/22:0) as a potential screening biomarker [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3025.